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Convolutional neural network ( CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections.
Here, the inductive bias is a logical formula that, together with the training data, logically entails the hypothesis generated by the learner. However, this strict formalism fails in many practical cases, where the inductive bias can only be given as a rough description (e.g. in the case of artificial neural networks), or not at all.
Cellular neural network. In computer science and machine learning, cellular neural networks ( CNN) or cellular nonlinear networks ( CNN) are a parallel computing paradigm similar to neural networks, with the difference that communication is allowed between neighbouring units only. Typical applications include image processing, analyzing 3D ...
Spiking neural network. The insect is controlled by a spiking neural network to find a target in an unknown terrain. Spiking neural networks ( SNNs) are artificial neural networks (ANN) that more closely mimic natural neural networks. [1] In addition to neuronal and synaptic state, SNNs incorporate the concept of time into their operating model.
A probabilistic neural network (PNN) [1] is a feedforward neural network, which is widely used in classification and pattern recognition problems. In the PNN algorithm, the parent probability distribution function (PDF) of each class is approximated by a Parzen window and a non-parametric function. Then, using PDF of each class, the class ...
There are many types of artificial neural networks ( ANN ). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey between input (such as from ...
A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either biological cells or mathematical models. While individual neurons are simple, many of them together in a network can perform complex tasks. There are two main types of neural network. In neuroscience, a biological neural ...
AlexNet is the name of a convolutional neural network (CNN) architecture, designed by Alex Krizhevsky in collaboration with Ilya Sutskever and Geoffrey Hinton, who was Krizhevsky's Ph.D. advisor at the University of Toronto. AlexNet competed in the ImageNet Large Scale Visual Recognition Challenge on September 30, 2012.